AI, Veterinary Tech, and the Tipping Point We’ve Reached

I’ve been thinking a lot about AI in veterinary over the past few months. Not in a “robots are coming for our jobs” way, but in a much more practical, slightly uncomfortable, very real way.

We’re at a tipping point.

And I don’t think the UK veterinary market is quite ready for what’s about to happen.

The flood is coming

Right now, we’re seeing a surge of AI-powered products aiming squarely at veterinary practices. Some are genuinely exciting. Some are… less so. And many are being built very quickly, often by teams outside the UK who don’t yet fully understand how UK practices actually work day-to-day.

What’s different this time is speed.

Not long ago, new veterinary software products took years to mature. AI has compressed that cycle dramatically. Tools can now be spun up, demoed, and sold in months, sometimes weeks, and that’s created a market where innovation is outpacing understanding.

That’s the dangerous bit.

AI is not the problem. Unclear value is.

Let me be clear: I’m pro‑AI.

Used well, AI has the potential to:

  • Reduce admin and cognitive load on teams

  • Improve clinical notes and record quality

  • Surface insights that are currently buried in systems

  • Help practices make better, faster decisions

But AI does not magically create value just because it exists.

A model that summarises a consult nobody has time to read. A chatbot bolted onto a broken workflow. A shiny dashboard with no clear action.

That’s not progress, it’s just noise.

Veterinary teams are already stretched. The bar for “this genuinely helps me” is extremely high, and rightly so.

The UK veterinary context really matters

This is the bit that often gets missed.

UK veterinary practice isn’t just a clone of the US, EU, or APAC markets. The regulatory environment, client expectations, pricing pressures, corporatisation, staffing challenges, they all shape how technology is adopted.

AI tools that ignore this reality risk becoming shelfware very quickly.

I’ve seen practices burned before:

  • Over‑promised implementations

  • Tools that don’t integrate cleanly with PMS platforms

  • Features that sound brilliant in a pitch deck but fall apart at 9am on a Monday

AI doesn’t get a free pass here. If anything, it needs more scrutiny.

Decision fatigue is the next big risk

What I’m already seeing:

Practice owners and managers are being asked to evaluate more tools, more demos, more promises, all while running a business and delivering clinical care.

Add AI into the mix and suddenly every product claims to be:

  • Smarter

  • Faster

  • Transformational

At some point, that becomes paralysing.

The risk isn’t that practices choose the wrong AI tool. It’s that they disengage altogether.

Where I think we need to land

For AI to genuinely succeed in UK veterinary, a few things need to happen:

  1. Problems first, AI second
    Start with the real operational or clinical pain, not the model.

  2. Integration over innovation
    If it doesn’t fit cleanly into existing systems and workflows, it won’t stick.

  3. Honest conversations
    What does this tool not do? Where does it struggle? What still needs a human?

  4. Guidance, not just software
    Practices need help navigating this landscape, not another login.

My slightly biased closing thought

AI in veterinary isn’t a fad, it’s inevitable.

But inevitability doesn’t equal inevitability of success.

We’re at the point where good decisions now will compound for years… and bad ones will be quietly expensive.

The practices that win won’t be the ones chasing every AI badge. They’ll be the ones who stay curious, sceptical, and focused on outcomes and not hype.

That’s the conversation I want to be part of.

If you’re a practice, a vendor, or a buying group wrestling with these questions, you’re not alone. We’re all figuring this out together — and that, honestly, is the interesting bit.

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Data Isn’t the Problem. What We Do With It Is.